Melt index detection fault diagnosis system and method for industrial polypropylene production

A melt index and fault detection technology, applied in general control systems, control/regulation systems, and comprehensive factory control, etc., can solve problems such as failure to take into account the multi-scale characteristics of the process and difficulty in obtaining fault diagnosis effects.

Inactive Publication Date: 2009-02-11
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the current fault diagnosis only considers the multicollinearity and nonlinear characteristics of the polypropylene production process, but does not consider the multi-scale characteristics of the process, and it is often difficult to obtain better fault diagnosis results.

Method used

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  • Melt index detection fault diagnosis system and method for industrial polypropylene production
  • Melt index detection fault diagnosis system and method for industrial polypropylene production
  • Melt index detection fault diagnosis system and method for industrial polypropylene production

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0092] refer to figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 as well as Figure 6 , industrial polypropylene production melt index detection fault diagnosis system, including on-site intelligent instrument 2 connected with polypropylene production process object 1, DCS system and host computer 6, said DCS system consists of data interface 3, control station 4, database 5 Composition; smart instrument 2, DCS system, and host computer 6 are connected in turn through the field bus, and the host computer 6 includes:

[0093] The standardization processing module 7 is used to standardize the data. The mean value of each variable is 0 and the variance is 1 to obtain the input matrix X. The following process is used to complete:

[0094] 1) Calculate the mean: TX ‾ = 1 N Σ i = 1 N ...

Embodiment 2

[0189] refer to figure 1 , figure 2 , image 3 as well as Figure 4 , a kind of industrial polypropylene production melt index detection fault diagnosis method, described fault diagnosis method comprises the following steps:

[0190] (1), determine the used key variable of fault diagnosis, collect the data of described variable when system is normal and fault respectively from the history database of DCS database as training sample TX;

[0191] (2), in wavelet decomposition module 8, principal component analysis module 9 and support vector machine classifier module 11, set respectively the parameters such as wavelet decomposition layer number, principal component analysis variance extraction rate, support vector machine kernel parameter and confidence probability, Set the sampling period in DCS;

[0192] (3), the training sample TX is in the upper computer 6, and the data is standardized, so that the mean value of each variable is 0, and the variance is 1, and the input m...

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Abstract

The present invention relates to an industrial polypropylene production melt index detection fault diagnosis system. Said system includes field intelligent instrument connected with industrial process object, DCS system and upper-position machine. The described DCS system is composed of data interface, control station and data base; the intelligent instrument, DCS system and upper-position machine are successively connected, and the described upper-position machine includes standardization processing module, wavelet decomposition module, pivot analysis function module, wavelet reconstruction function module, support vector machine classifier function module and fault judgement module. Besides, said invention also provides a fault diagnosis method.

Description

(1) Technical field [0001] The invention relates to the field of industrial process fault diagnosis, in particular to a fault diagnosis system and method for industrial polypropylene production melt index detection. (2) Background technology [0002] Polypropylene is a synthetic resin mainly polymerized from propylene monomer, and is an important product in the plastics industry. Among the polyolefin resins in my country, it has become the third largest plastic after polyethylene and polyvinyl chloride. In the production process of polypropylene, melt index (MI) is an important index reflecting product quality and an important basis for production quality control and brand switching. However, MI can only be detected offline. Generally, offline analysis takes at least 2 hours, which is costly and time-consuming. Especially during the 2 hours of offline analysis, it will not be possible to know the status of the polypropylene production process in time. Therefore, it is extr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B19/048G05B19/418G05B13/02G06F17/00G01N25/04
CPCY02P90/02
Inventor 刘兴高
Owner ZHEJIANG UNIV
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